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digitalmars.D.announce - matrix library

reply Vlad Levenfeld <vlevenfeld gmail.com> writes:
https://github.com/evenex/linalg

I've some heard people (including me) asking about matrix 
libraries for D, and while there is gl3n it only goes to 4x4 
matrices and was written before all the multidimensional indexing 
stuff.

So I was using gl3n for awhile until I needed some 6x6s and threw 
together a syntax-sugary sort of wrapper over 
std.experimental.ndslice and cblas for matrix math.

You can slice submatrices, assign to them, and perform ops on 
them with other matrices or 2-dimensional array slices... though, 
for implementation-ish reasons, ops involving 2-d arrays are 
elementwise (you'll have to call the Matrix constructor to use 
matrix multiplication again).

It was built in kind of an ad-hoc way and I will be adding stuff 
to it as the need arises, so there's nothing there yet beyond the 
bare basics and you should expect bugs. All the matrices hold 
static arrays because I don't want to mess with reference 
problems right now. A matrix past a certain size will be more 
efficient to store as a dynamic array, of course. But, right now, 
I need this to make writing linear algebra code comfortable for 
myself rather than try to win at benchmarks.

Bugs/Pull/Feature requests welcome.
May 23 2016
next sibling parent reply Carl Vogel <carljv gmail.com> writes:
On Monday, 23 May 2016 at 07:28:20 UTC, Vlad Levenfeld wrote:

 https://github.com/evenex/linalg

 I've some heard people (including me) asking about matrix 
 libraries for D, and while there is gl3n it only goes to 4x4 
 matrices and was written before all the multidimensional 
 indexing stuff.

 So I was using gl3n for awhile until I needed some 6x6s and 
 threw together a syntax-sugary sort of wrapper over 
 std.experimental.ndslice and cblas for matrix math.

 You can slice submatrices, assign to them, and perform ops on 
 them with other matrices or 2-dimensional array slices... 
 though, for implementation-ish reasons, ops involving 2-d 
 arrays are elementwise (you'll have to call the Matrix 
 constructor to use matrix multiplication again).

 It was built in kind of an ad-hoc way and I will be adding 
 stuff to it as the need arises, so there's nothing there yet 
 beyond the bare basics and you should expect bugs. All the 
 matrices hold static arrays because I don't want to mess with 
 reference problems right now. A matrix past a certain size will 
 be more efficient to store as a dynamic array, of course. But, 
 right now, I need this to make writing linear algebra code 
 comfortable for myself rather than try to win at benchmarks.

 Bugs/Pull/Feature requests welcome.


This is nice! I recently found myself having to make ad hoc 
lightweight matrix classes that wrap some blas functions. Making 
the dims template/compile-time params is an interesting choice, 
but I wonder if it is unduly limiting.

How does what you're doing compare to what's in 
https://github.com/DlangScience/scid/blob/master/source/scid/linalg.d ? While
that project doesn't have a ton of manpower behind it, it does seem like it's
actively maintained, and they have brought in a ton of the lapack/blas headers
already. It would be nice, and I think do-able, to have a relatively complete
and performant library for matrices/ndarrays, especially given the recent work
on ndslice. (If there are plans or a roadmap for this sort of thing, I'd love
to contribute, and it seems from this announcement that others are interested
also.)
May 23 2016
parent reply Vlad Levenfeld <vlevenfeld gmail.com> writes:
On Monday, 23 May 2016 at 18:10:40 UTC, Carl Vogel wrote:

 How does what you're doing compare to what's in 
 https://github.com/DlangScience/scid/blob/master/source/scid/linalg.d ?


Basically, I have made a matrix structure and wrapped some basic 
arithmetic, while scid.linalg provides functions wrapping some 
heavier tasks (inversion, determinant, etc).
There appears to be no functional overlap, and I think what I 
will do is contribute any actual linalg routines I write back to 
scid.linalg, and then import it as a dependency to this package.
The stuff in my lib right now is way less careful wrt resources 
than scid.linalg and wouldn't serve as a general-purpose matrix 
wrapper. Maybe in enough iterations it will converge on something 
relatively performant.

On Monday, 23 May 2016 at 18:10:40 UTC, Carl Vogel wrote:

 Making the dims template/compile-time params is an interesting 
 choice, but I wonder if it is unduly limiting.


Yeah, you are right. I mentioned dynamic-array-backed matrices as 
an efficiency thing in my first post but that would be a good way 
to solve this problem as well.
May 23 2016
parent reply Vlad Levenfeld <vlevenfeld gmail.com> writes:
On Monday, 23 May 2016 at 20:11:22 UTC, Vlad Levenfeld wrote:

 ...


On first glance it looks like 
https://github.com/DlangScience/scid/blob/master/source/scid/matrix.d has most
of what my matrix implementation is missing. Not sure how to put them together
yet.
May 23 2016
parent reply Edwin van Leeuwen <edder tkwsping.nl> writes:
On Monday, 23 May 2016 at 20:27:54 UTC, Vlad Levenfeld wrote:

 On Monday, 23 May 2016 at 20:11:22 UTC, Vlad Levenfeld wrote:

 ...


 On first glance it looks like 
 https://github.com/DlangScience/scid/blob/master/source/scid/matrix.d has most
of what my matrix implementation is missing. Not sure how to put them together
yet.


There is also mir, which is working towards being a full 
replacement for blas:
https://github.com/libmir/mir

It is still under development, but I think the goal is to become 
the ultimate matrix library :)
May 23 2016
parent reply Vlad Levenfeld <vlevenfeld gmail.com> writes:
On Monday, 23 May 2016 at 20:56:54 UTC, Edwin van Leeuwen wrote:

 There is also mir, which is working towards being a full 
 replacement for blas:
 https://github.com/libmir/mir

 It is still under development, but I think the goal is to 
 become the ultimate matrix library :)


I am sorely tempted to use mir's MatrixView as the backend for 
the matrix slicing but don't know what else I might need from 
cblas, so maybe this will come later (especially when I figure 
out, or someone explains, what the proper resource/reference 
handling should be, especially in the case of small matrices 
backed by static arrays or something).

Now I am thinking that the best way to orthogonalize (sorry) my 
efforts with respect to mir and scid.linalg is to use them as 
backend drivers, maintain this wrapper for the crowd that isn't 
as familiar with blas/lapack, or wants to write slightly more 
concise top-level code, and forward the relevant bug reports and 
pull requests to mir and scid.
May 23 2016
parent reply Edwin van Leeuwen <edder tkwsping.nl> writes:
On Monday, 23 May 2016 at 23:08:46 UTC, Vlad Levenfeld wrote:

 Now I am thinking that the best way to orthogonalize (sorry) my 
 efforts with respect to mir and scid.linalg is to use them as 
 backend drivers, maintain this wrapper for the crowd that isn't 
 as familiar with blas/lapack, or wants to write slightly more 
 concise top-level code, and forward the relevant bug reports 
 and pull requests to mir and scid.


You might be interested in joining the gitter channel where the 
mir developers hang out:
https://gitter.im/libmir/public
May 23 2016
parent reply Vlad Levenfeld <vlevenfeld gmail.com> writes:
On Tuesday, 24 May 2016 at 05:52:03 UTC, Edwin van Leeuwen wrote:

 You might be interested in joining the gitter channel where the 
 mir developers hang out:
 https://gitter.im/libmir/public


Thanks!
May 24 2016
parent Seb <seb wilzba.ch> writes:
On Tuesday, 24 May 2016 at 07:53:15 UTC, Vlad Levenfeld wrote:

 On Tuesday, 24 May 2016 at 05:52:03 UTC, Edwin van Leeuwen 
 wrote:

 You might be interested in joining the gitter channel where 
 the mir developers hang out:
 https://gitter.im/libmir/public


 Thanks!


Yes you are very welcome  gitter / mir!

Btw as said Ilya is working on full BLAS support.
There are a couple of issue floating around in the libmir issue 
tracker,
but probably the best one to track is this:

https://github.com/libmir/mir/issues/48
May 24 2016
prev sibling next sibling parent Ilya Yaroshenko <ilyayaroshenko gmail.com> writes:
On Monday, 23 May 2016 at 07:28:20 UTC, Vlad Levenfeld wrote:

 https://github.com/evenex/linalg

 I've some heard people (including me) asking about matrix 
 libraries for D, and while there is gl3n it only goes to 4x4 
 matrices and was written before all the multidimensional 
 indexing stuff.

 [...]


Generic matrix-matrix multiplication is available in Mir  version 
0.16.0-beta2
http://docs.mir.dlang.io/latest/mir_glas_gemm.html
It should be compiled with recent LDC beta, and -mcpu=native flag.
Aug 22 2016
prev sibling parent reply Ilya Yaroshenko <ilyayaroshenko gmail.com> writes:
On Monday, 23 May 2016 at 07:28:20 UTC, Vlad Levenfeld wrote:

 https://github.com/evenex/linalg

 I've some heard people (including me) asking about matrix 
 libraries for D, and while there is gl3n it only goes to 4x4 
 matrices and was written before all the multidimensional 
 indexing stuff.

 So I was using gl3n for awhile until I needed some 6x6s and 
 threw together a syntax-sugary sort of wrapper over 
 std.experimental.ndslice and cblas for matrix math.


Generic matrix-matrix multiplication is available in Mir version 
0.16.0-beta2
http://docs.mir.dlang.io/latest/mir_glas_gemm.html
It should be compiled with recent LDC beta, and -mcpu=native flag.
Aug 22 2016
parent jmh530 <john.michael.hall gmail.com> writes:
On Tuesday, 23 August 2016 at 06:18:54 UTC, Ilya Yaroshenko wrote:

 Generic matrix-matrix multiplication is available in Mir 
 version 0.16.0-beta2
 http://docs.mir.dlang.io/latest/mir_glas_gemm.html
 It should be compiled with recent LDC beta, and -mcpu=native 
 flag.


Glad you are making progress on this front.
Aug 23 2016